On the anti-rolling performance of a train using a vortex generator array

Bin Xu, Xiaodong Chen, Tanghong Liu, Zhengwei Chen, Wenhui Li, Yutao Xia, Xiaoshuai Huo, Hongrui Gao, Hongkang Liu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Vortex generators (VGs) have shown the potential to mitigate the train's operational instability issues caused by strong wind. Numerical simulations are used to predict the flow structures around a train with VGs of different heights. The improved delayed detached eddy simulation (IDDES) hybrid modeling method is adopted to predict the trailing vortices on the leeward field. The numerical method is validated by reproducing wind tunnel test results. The study results reveal that VGs are capable of reducing the rolling moment coefficient around the leeward rail of a train by about 5% ∼ 15% while keeping the drag of the train still lower than its operational drag without crosswind. The control mechanism lies on that the streamwise vortices generated by VGs are attracted to the large-scale trailing vortices, resulting in the pressure on the leeward wall rising. The differences in the domain frequencies between VGs and Baseline cases in POD modes indicate that the VGs changed the periodicity and symmetry of the vorticity fluctuation. This study provides a new method to improve the safety of trains under crosswinds.

Original languageEnglish
Article number2275614
JournalEngineering Applications of Computational Fluid Mechanics
Volume17
Issue number1
DOIs
Publication statusPublished - 2023

Keywords

  • computational fluid dynamics
  • crosswind
  • proper orthogonal decomposition
  • Train

ASJC Scopus subject areas

  • General Computer Science
  • Modelling and Simulation

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